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Current Result Document :
1
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´ÙÀ½°Ç
ÇѱÛÁ¦¸ñ(Korean Title)
½Å¹®±â»ç¿Í ¼Ò¼È ¹Ìµð¾î¸¦ È°¿ëÇÑ Çѱ¹¾î ¹®¼¿ä¾à µ¥ÀÌÅÍ ±¸Ãà
¿µ¹®Á¦¸ñ(English Title)
Building a Korean Text Summarization Dataset Using News Articles of Social Media
ÀúÀÚ(Author)
Gyoung Ho Lee
Yo-Han Park
Kong Joo Lee
ÀÌ°æÈ£
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ÀÌ°øÁÖ
¿ø¹®¼ö·Ïó(Citation)
VOL 09 NO. 08 PP. 0251 ~ 0258 (2020. 08)
Çѱ۳»¿ë
(Korean Abstract)
¹®¼ ¿ä¾àÀ» À§ÇÑ ÇнÀ µ¥ÀÌÅÍ´Â ¹®¼¿Í ±× ¿ä¾àÀ¸·Î ±¸¼ºµÈ´Ù. ±âÁ¸ÀÇ ¹®¼ ¿ä¾à µ¥ÀÌÅÍ´Â »ç¶÷ÀÌ ¼öµ¿À¸·Î ¿ä¾àÀ» ÀÛ¼ºÇÏ¿´±â ¶§¹®¿¡ ´ë·®ÀÇ µ¥ÀÌÅÍ È®º¸°¡ ¾î·Á¿ü´Ù. ±×·¸±â ¶§¹®¿¡ ¿Â¶óÀÎÀ¸·Î ½±°Ô ¼öÁý °¡´ÉÇÏ¸ç ¹®¼ÀÇ Ç°ÁúÀÌ ¿ì¼öÇÑ ÀÎÅÍ³Ý ½Å¹®±â»ç°¡ ¹®¼ ¿ä¾à ¿¬±¸¿¡ ¸¹ÀÌ È°¿ëµÇ¾î ¿Ô´Ù. º» ¿¬±¸¿¡¼´Â ¾ð·Ð»ç°¡ ¼Ò¼È ¹Ìµð¾î¿¡ °Ô½ÃÇÑ ¼³¸í±Û°ú Á¦¸ñ, ºÎÁ¦¸¦ º»¹®ÀÇ ¿ä¾àÀ¸·Î »ç¿ëÇÏ¿© Çѱ¹¾î ¹®¼ ¿ä¾à µ¥ÀÌÅ͸¦ ±¸¼ºÇÏ´Â °ÍÀ» Á¦¾ÈÇÑ´Ù. ¾à 425,000°³ÀÇ ½Å¹®±â»ç¿Í ±× ¿ä¾àµ¥ÀÌÅ͸¦ ±¸ÃàÇÒ ¼ö ÀÖ¾ú´Ù. ±¸¼ºÇÑ µ¥ÀÌÅÍÀÇ À¯¿ë¼ºÀ» º¸À̱â À§ÇØ ÃßÃâ ¿ä¾à ½Ã½ºÅÛÀ» ±¸ÇöÇÏ¿´´Ù. º» ¿¬±¸¿¡¼ ±¸ÃàÇÑ µ¥ÀÌÅÍ·Î ÇнÀÇÑ ±³»ç ÇнÀ ¸ðµ¨°ú ºñ±³»ç ÇнÀ ¸ðµ¨ÀÇ ¼º´ÉÀ» ºñ±³ÇÏ¿´´Ù. ½ÇÇè °á°ú Á¦¾ÈÇÑ µ¥ÀÌÅÍ·Î ÇнÀÇÑ ¸ðµ¨ÀÌ ºñ±³»ç ÇнÀ ¾Ë°í¸®Áò¿¡ ºñÇØ ´õ ³ôÀº ROUGE Á¡¼ö¸¦ º¸¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
A training dataset for text summarization consists of pairs of a document and its summary. As conventional approaches to building text summarization dataset are human labor intensive, it is not easy to construct large datasets for text summarization. A collection of news articles is one of the most popular resources for text summarization because it is easily accessible, large-scale and high-quality text. From social media news services, we can collect not only headlines and subheads of news articles but also summary descriptions that human editors write about the news articles. Approximately 425,000 pairs of news articles and their summaries are collected from social media. We implemented an automatic extractive summarizer and trained it on the dataset. The performance of the summarizer is compared with unsupervised models. The summarizer achieved better results than unsupervised models in terms of ROUGE score.
Å°¿öµå(Keyword)
Korean Text Summarization Dataset
Description
Headline
Subhead
Automatic Extractive Summarization
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